Thus, the reasoning done in [1]} on the EEG embeddings in [2]} looks very much like a straw man argument: indeed, contrary to what is stated in [1]}, we did not say in [2]} that the regression from pre-trained visual features to the EEG features should result in a benefit to classification accuracy. On the contrary, we clearly show in [2]} (in Table 5) that performance drops when moving from visual to brain-derived features. What is clear from [2]} is that the regression from visual features to brain-derived features is a simple but effective strategy to employ EEG features that are useful for visual categorization, and not to improve performance of visual classifiers. This point cannot be refuted.
